A Comparative Study of Weighted Recursive Least Square Algorithm and Variable Forgetting Factor Recursive Least Square Algorithm for Parameter Estimation of Lithium-Ion Battery
This paper focuses on the development of a lithium-ion (Li-ion) battery model using a Thevenin circuit to analyze its immediate and transient response. The battery model is utilized alongside a Weighted Recursive Least Square (WRLS) algorithm for estimating battery parameters. The performance of thi...
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| Veröffentlicht in: | 2024 International Telecommunications Conference (ITC-Egypt) S. 416 - 422 |
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22.07.2024
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| Abstract | This paper focuses on the development of a lithium-ion (Li-ion) battery model using a Thevenin circuit to analyze its immediate and transient response. The battery model is utilized alongside a Weighted Recursive Least Square (WRLS) algorithm for estimating battery parameters. The performance of this algorithm is then compared to the Variable Forgetting Factor Recursive Least Square (VFFRLS) algorithm. The comparison between the two algorithms demonstrates that WRLS outperforms VFFRLS, exhibiting lower error and superior performance. This finding establishes the reliability and effectiveness of WRLS for accurately estimating parameters in Li-ion batteries. The simulations and data processing are conducted using MATLAB/Simulink, while the dataset utilized is obtained from CALCE, a leading institution specializing in reliability engineering and failure analysis. The simulated terminal voltage is compared with the actual terminal voltage to validate the accuracy and credibility of both algorithms. |
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| AbstractList | This paper focuses on the development of a lithium-ion (Li-ion) battery model using a Thevenin circuit to analyze its immediate and transient response. The battery model is utilized alongside a Weighted Recursive Least Square (WRLS) algorithm for estimating battery parameters. The performance of this algorithm is then compared to the Variable Forgetting Factor Recursive Least Square (VFFRLS) algorithm. The comparison between the two algorithms demonstrates that WRLS outperforms VFFRLS, exhibiting lower error and superior performance. This finding establishes the reliability and effectiveness of WRLS for accurately estimating parameters in Li-ion batteries. The simulations and data processing are conducted using MATLAB/Simulink, while the dataset utilized is obtained from CALCE, a leading institution specializing in reliability engineering and failure analysis. The simulated terminal voltage is compared with the actual terminal voltage to validate the accuracy and credibility of both algorithms. |
| Author | Hamdy, Ragi A. Abdel-Khalik, Ayman S. Ghaly, Engy A. |
| Author_xml | – sequence: 1 givenname: Engy A. surname: Ghaly fullname: Ghaly, Engy A. email: eng-Engy.Ghaly1318@alexu.edu.eg organization: Alexandria University,Department of Electrical Engineering,Alexandria,Egypt – sequence: 2 givenname: Ayman S. surname: Abdel-Khalik fullname: Abdel-Khalik, Ayman S. email: ayman.abdel-khalik@alexu.edu.eg organization: Alexandria University,Department of Electrical Engineering,Alexandria,Egypt – sequence: 3 givenname: Ragi A. surname: Hamdy fullname: Hamdy, Ragi A. email: rhamdy@alexu.edu.eg organization: Alexandria University,Department of Electrical Engineering,Alexandria,Egypt |
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| Snippet | This paper focuses on the development of a lithium-ion (Li-ion) battery model using a Thevenin circuit to analyze its immediate and transient response. The... |
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| SubjectTerms | Accuracy Analytical models Lithium-ion batteries Lithium-Ion battery (Li-ion) Parameter estimation Prediction algorithms Transient response Variable Forgetting Factor Recursive Least Square (VFFRLS) Voltage Weighted Recursive Least Square (WRLS) |
| Title | A Comparative Study of Weighted Recursive Least Square Algorithm and Variable Forgetting Factor Recursive Least Square Algorithm for Parameter Estimation of Lithium-Ion Battery |
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